Top Machine Learning Engineer Jobs in San Francisco Bay Area, CA

In this role, you will lead AI personalization initiatives, develop AI/ML models for user experience, collaborate across teams, and ensure rigorous development practices.

The Senior Lead Machine Learning Engineer will design, develop, and implement machine learning systems, collaborating with teams to solve business problems using machine learning applications.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

The Principal Engineer, AI/ML Architecture will define the technical direction for Coupa's AI platform, focusing on model training, evaluation, safety standards, and mentoring a team of ML and data engineers.

Responsible for designing and implementing reinforcement learning algorithms, conducting experiments, and optimizing models for robotic applications, collaborating with multiple teams.

As a Machine Learning Engineer, you will build end-to-end ML systems for autonomous underwriting, collaborating with underwriters and engineers to advance ML capability.

The role involves building ML systems, improving models across product surfaces, and leveraging data for personalization and user engagement.

As a Machine Learning Engineer, you'll own the design, development, and operation of production-grade ML systems in clinical workflows, ensuring model accuracy, reliability, and integration into patient-facing applications.

Develop and optimize machine learning models for data extraction from tax documents, collaborate on software integration, and mentor junior team members.

As the founding Machine Learning Engineer, you'll own end-to-end credit risk modeling, from data pipeline design to production deployment, collaborating with cross-functional teams to shape modeling decisions and define future hires.

The Machine Learning Engineer will build and maintain data pipelines for ML training datasets, contribute to distributed training workflows, and enhance the ML platform's reliability and efficiency.

The Staff Machine Learning Engineer will fine-tune LLMs for healthcare workflows, develop training datasets, create evaluation frameworks, and collaborate with experts to improve model behavior.

Citizen Health seeks AI/Machine Learning Engineers to develop AI solutions for healthcare using advanced ML techniques, focusing on rare diseases and patient care. Responsibilities include designing ML models, optimizing LLMs, and ensuring compliance.

The Applied Machine Learning Engineer will build end-to-end ML pipelines, extract insights from data, and optimize systems, primarily using Python and SQL.

As a Machine Learning Engineer, you will apply ML techniques for perception tasks, develop model training methods, and evaluate performance in autonomous driving applications.

Design and build foundation-scale datasets and training recipes; develop human and machine labeling methods; create continuous data intake and automated data collection/model update pipelines; evaluate real-world model performance and detect regressions; maintain ground-truth-free performance metrics.

The AI/ML Engineer will design and deploy advanced AI models, optimize performance, and directly engage with government officials to transform industries through innovative AI solutions.

The ML Engineer will develop applications for biomarker and target discovery, supporting scientists with multi-step workflows and analyses in drug development.

As a Machine Learning Engineer, develop ML models, data pipelines, conduct analytics, and work on image and video inference for fish health and behavior.

As a Staff ML Engineer, you'll lead complex model quality improvements in clinical AI, spanning research and engineering, optimizing performance under high compliance conditions.

As a Machine Learning Engineer, you will design and deploy models, collaborate with teams to solve business challenges, optimize performance, and maintain model effectiveness.

Develop advanced multimodal large language models for autonomous driving, optimize solutions using real-world scenarios, and collaborate with engineering teams.

As a Senior Staff Machine Learning Engineer at Affirm, you will lead complex ML system design and implementation, mentor engineers, and drive innovative ML strategies for financial services.

Lead the development of software infrastructure for protein design pipelines, ensuring reliable integration of ML systems and experimental workflows.

The ML Engineer will design, develop, and deploy AI-native ML systems for demand forecasting and labor optimization, owning the entire ML lifecycle from data ingestion to monitoring.